Browser Use is an open-source Python library that enables LLM-based agents to operate web browsers and interact with web applications. It can navigate, enter data, extract text and manage multiple tabs to coordinate actions across applications. The library is particularly useful when AI agents need to access, manipulate or retrieve information from web content. It supports a range of LLMs and leverages Playwright to combine visual understanding with HTML structure extraction for richer web interactions. Our teams integrated Browser Use with the Pytest framework and Allure reporting to explore automated testing with LLMs. Test steps were written in natural language for the agent to execute, capturing screenshots on assertions or failures. The goal was to enable off-hours QA by automatically pulling test cases from Confluence for post-development verification. Early results are promising, though the agent's post-task responses often lack detailed failure descriptions, so require custom error reporting.
Browser Use is an open-source python library that enables LLM-based AI agents to use web browsers and access web applications. It can control the browser and perform steps that include navigations, inputs and text extractions. With the ability to manage multiple tabs, it can perform coordinated actions across multiple web apps. It’s useful for scenarios where LLM-based agents need to access web content, perform actions on it and get the results. The library can work with a variety of LLMs. It leverages Playwright to control the browser, combining visual understanding with HTML structure extraction for improved web interaction. This library is gaining traction in multi-agent scenarios, enabling agents to collaborate on complex workflows involving web interactions.
